导入方式修改

backend/app/main_graph/nodes/_utils.py

@@ -4,12 +4,13 @@
 """
 
 from typing import Dict, Any, Optional
+from langchain_core.runnables.config import RunnableConfig
 
 
 async def dispatch_custom_event(
     event_name: str,
     data: Dict[str, Any],
-    config: Optional[Dict[str, Any]] = None,
+    config: Optional[RunnableConfig] = None,
 ) -> None:
     """
     安全地发送自定义事件，忽略发送失败

backend/app/main_graph/nodes/error_handling.py

@@ -2,8 +2,8 @@
 错误处理节点 - 处理子图/工具调用错误
 """
 
-from app.main_graph.state import MainGraphState, ErrorSeverity
-from app.logger import info
+from ...main_graph.state import MainGraphState, ErrorSeverity
+from ...logger import info
 
 
 def error_handling_node(state: MainGraphState) -> MainGraphState:

backend/app/main_graph/nodes/fast_paths.py

@@ -4,6 +4,7 @@
 """
 
 from typing import Optional
+from langchain_core.runnables.config import RunnableConfig
 
 from ..state import MainGraphState
 from ...logger import info, debug
@@ -28,7 +29,7 @@ CHITCHAT_KEYWORDS = {
 
 
 # ========== 闲聊节点 ==========
-async def fast_chitchat_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def fast_chitchat_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """快速闲聊节点"""
     state.current_phase = "fast_chitchat"
     query = state.user_query or ""
@@ -69,14 +70,14 @@ def _match_chitchat_template(query: str) -> str:
 
 
 # ========== 快速 RAG 节点 ==========
-async def fast_rag_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def fast_rag_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """快速 RAG 节点：只负责 RAG 检索，然后交给 llm_call 生成回答"""
     state.current_phase = "fast_rag"
     query = state.user_query or ""
     info(f"[Fast RAG] 开始处理: {query[:50]}")
 
     # 获取 RAG 工具
-    from app.main_graph.utils.rag_initializer import get_rag_tool
+    from backend.app.main_graph.utils.rag_initializer import get_rag_tool
     rag_tool = get_rag_tool()
     info(f"[Fast RAG] 获取到 rag_tool: {rag_tool is not None}")
 
@@ -134,7 +135,7 @@ async def _generate_fast_answer(state: MainGraphState, query: str) -> MainGraphS
 请给出简洁、准确的回答："""
 
         # 使用流式输出
-        from app.main_graph.config import get_stream_writer
+        from backend.app.main_graph.config import get_stream_writer
         writer = get_stream_writer()
 
         full_content = ""
@@ -164,7 +165,7 @@ async def _generate_fast_answer(state: MainGraphState, query: str) -> MainGraphS
 
 
 # ========== 快速工具节点 ==========
-async def fast_tool_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def fast_tool_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """快速工具节点"""
     state.current_phase = "fast_tool"
 

backend/app/main_graph/nodes/finalize.py

@@ -6,9 +6,9 @@
 from typing import Any, Dict
 
 # 本地模块
-from app.main_graph.state import MainGraphState
-from app.utils.logging import log_state_change
-from app.logger import info, warning
+from ...main_graph.state import MainGraphState
+from ...utils.logging import log_state_change
+from ...logger import info, warning
 
 from langchain_core.runnables.config import RunnableConfig
 
@@ -35,7 +35,7 @@ async def finalize_node(state: MainGraphState, config: RunnableConfig) -> Dict[s
 
     try:
         # 获取流式写入器并发送完成事件
-        from app.main_graph.config import get_stream_writer
+        from backend.app.main_graph.config import get_stream_writer
         writer = get_stream_writer()
 
         # 只在 writer 存在且不是 noop 时才发送

backend/app/main_graph/nodes/hybrid_router.py

@@ -8,6 +8,7 @@ import json
 from typing import Optional
 from dataclasses import dataclass, field
 from datetime import datetime
+from langchain_core.runnables.config import RunnableConfig
 
 from ..state import MainGraphState
 from ...logger import info, debug
@@ -157,7 +158,7 @@ def _default_result() -> HybridRouterResult:
 
 
 # ========== 主路由节点 ==========
-async def hybrid_router_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def hybrid_router_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """混合路由节点：前置路由，决定走快速路径还是 React 循环"""
     state.current_phase = "hybrid_router"
     query = state.user_query or ""

backend/app/main_graph/nodes/llm_call.py

@@ -9,10 +9,10 @@ from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import AIMessage
 
 # 本地模块
-from app.main_graph.state import MainGraphState
-from app.agent.prompts import create_system_prompt
-from app.utils.logging import log_state_change
-from app.logger import debug, info, error
+from ...main_graph.state import MainGraphState
+from ...agent.prompts import create_system_prompt
+from ...utils.logging import log_state_change
+from ...logger import debug, info, error
 
 
 def create_dynamic_llm_call_node(chat_services: Dict[str, BaseChatModel], tools: list):
@@ -82,6 +82,12 @@ def create_dynamic_llm_call_node(chat_services: Dict[str, BaseChatModel], tools:
         try:
             # 添加上下文到消息
             messages_with_context = list(state.messages)
+            info(f"[llm_call] 原始消息数量: {len(messages_with_context)}")
+            for i, msg in enumerate(messages_with_context):
+                msg_type = getattr(msg, 'type', 'unknown')
+                msg_content = getattr(msg, 'content', '')[:100] if hasattr(msg, 'content') else str(msg)[:100]
+                info(f"[llm_call]   msg[{i}] type={msg_type}, content={repr(msg_content)}")
+
             if state.rag_context:
                 from langchain_core.messages import SystemMessage
                 rag_system_msg = SystemMessage(content=f"以下是检索到的相关信息：\n{state.rag_context}")
@@ -93,11 +99,13 @@ def create_dynamic_llm_call_node(chat_services: Dict[str, BaseChatModel], tools:
                         break
                 if not inserted:
                     messages_with_context.insert(0, rag_system_msg)
-            
+                info(f"[llm_call] RAG上下文已添加，长度: {len(state.rag_context)}")
+
             # 恢复为：手动进行 astream，并将所有的 chunk 拼接成最终的 response 返回。
             # LangGraph 会自动监听这期间产生的所有 token。
             chain = prompt | llm_with_tools
             chunks = []
+            info(f"[llm_call] 开始调用 LLM astream...")
             async for chunk in chain.astream(
                 {
                     "messages": messages_with_context,
@@ -106,7 +114,26 @@ def create_dynamic_llm_call_node(chat_services: Dict[str, BaseChatModel], tools:
                 config=config
             ):
                 chunks.append(chunk)
-            
+
+            info(f"[llm_call] LLM astream 完成，共收到 {len(chunks)} 个 chunks")
+            for i, chunk in enumerate(chunks[:10]):  # 只打印前10个避免日志过多
+                chunk_type = type(chunk).__name__
+                chunk_content = getattr(chunk, 'content', '') if hasattr(chunk, 'content') else str(chunk)
+                # 打印更多属性
+                additional_kwargs = getattr(chunk, 'additional_kwargs', {}) or {}
+                response_metadata = getattr(chunk, 'response_metadata', {}) or {}
+                # 打印所有属性
+                info(f"[llm_call]   chunk[{i}] type={chunk_type}")
+                info(f"[llm_call]   chunk[{i}] content长度={len(chunk_content) if chunk_content else 0}, content={repr(chunk_content[:200] if chunk_content else '')}")
+                info(f"[llm_call]   chunk[{i}] additional_kwargs={additional_kwargs}")
+                info(f"[llm_call]   chunk[{i}] response_metadata keys={list(response_metadata.keys()) if response_metadata else []}")
+                info(f"[llm_call]   chunk[{i}] response_metadata={response_metadata}")
+                # 检查是否有其他可能存储内容的属性
+                if hasattr(chunk, 'tool_call_chunks'):
+                    info(f"[llm_call]   chunk[{i}] tool_call_chunks={chunk.tool_call_chunks}")
+                if hasattr(chunk, 'usage_metadata'):
+                    info(f"[llm_call]   chunk[{i}] usage_metadata={chunk.usage_metadata}")
+
             # 将所有 chunk 合并成最终的 AIMessage
             if chunks:
                 response = chunks[0]
@@ -114,6 +141,7 @@ def create_dynamic_llm_call_node(chat_services: Dict[str, BaseChatModel], tools:
                     response = response + chunk
             else:
                 response = AIMessage(content="")
+                info(f"[llm_call] ⚠️ 警告: 没有收到任何 chunks！")
             
             elapsed_time = time.time() - start_time
             

backend/app/main_graph/nodes/memory_trigger.py

@@ -1,8 +1,8 @@
 from typing import Any, Dict
 from langchain_core.runnables.config import RunnableConfig
-from app.main_graph.state import MainGraphState
-from app.memory.mem0_client import Mem0Client
-from app.logger import info
+from ...main_graph.state import MainGraphState
+from ...memory.mem0_client import Mem0Client
+from ...logger import info
 
 
 # 全局变量，在 GraphBuilder 中注入

backend/app/main_graph/nodes/rag_nodes.py

@@ -7,16 +7,17 @@ import time
 import asyncio
 from typing import Optional
 from datetime import datetime
+from langchain_core.runnables.config import RunnableConfig
 
-from app.main_graph.state import MainGraphState, ErrorRecord, ErrorSeverity
-from app.main_graph.utils.retry_utils import RAG_RETRY_CONFIG
-from app.logger import info
+from ...main_graph.state import MainGraphState, ErrorRecord, ErrorSeverity
+from ...main_graph.utils.retry_utils import RAG_RETRY_CONFIG
+from ...logger import info
 from ._utils import dispatch_custom_event, make_react_event
 
 
 def _get_rag_tool() -> Optional[callable]:
     """获取 RAG 工具"""
-    from app.main_graph.utils.rag_initializer import get_rag_tool
+    from backend.app.main_graph.utils.rag_initializer import get_rag_tool
     return get_rag_tool()
 
 
@@ -35,6 +36,9 @@ async def _rag_retrieve_core(state: MainGraphState, rag_tool: callable) -> MainG
     # 调用 RAG 工具
     rag_context = await rag_tool.ainvoke(retrieval_query)
     info(f"[RAG Core] 获取到 rag_context: {type(rag_context)}, 长度={len(rag_context) if rag_context else 0}")
+    info(f"[RAG Core] ========== RAG 返回的知识内容 ==========")
+    info(f"{rag_context[:500]}..." if len(rag_context) > 500 else rag_context)
+    info(f"[RAG Core] ========================================")
 
     state.rag_context = rag_context
     state.rag_docs = [{"source": "rag_retrieval", "content": rag_context}]
@@ -47,7 +51,7 @@ async def _rag_retrieve_core(state: MainGraphState, rag_tool: callable) -> MainG
 
 
 # ========== RAG 检索节点 ==========
-async def rag_retrieve_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def rag_retrieve_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """RAG 检索节点：带超时和重试"""
     state.current_phase = "rag_retrieving"
     start_time = time.time()
@@ -156,7 +160,7 @@ async def rag_retrieve_node(state: MainGraphState, config: Optional[dict] = None
     return state
 
 
-async def rag_re_retrieve_node(state: MainGraphState, config: Optional[dict] = None) -> MainGraphState:
+async def rag_re_retrieve_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """重新检索节点"""
     state.current_phase = "rag_re_retrieving"
 

backend/app/main_graph/nodes/reasoning.py

@@ -3,16 +3,17 @@ React 推理节点
 使用 intent.py 进行意图推理
 """
 
-from typing import Dict, Any, Optional
+from typing import Optional
 from datetime import datetime
+from langchain_core.runnables.config import RunnableConfig
 
-from app.core.intent import react_reason_async, ReasoningResult
-from app.main_graph.state import MainGraphState
-from app.logger import info
+from ...core.intent import react_reason_async, ReasoningResult
+from ...main_graph.state import MainGraphState
+from ...logger import info
 from ._utils import dispatch_custom_event, make_react_event
 
 
-async def react_reason_node(state: MainGraphState, config: Optional[Dict[str, Any]] = None) -> MainGraphState:
+async def react_reason_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """React 模式推理节点：判断下一步做什么"""
     state.current_phase = "react_reasoning"
     state.reasoning_step += 1

backend/app/main_graph/nodes/retrieve_memory.py

@@ -6,10 +6,10 @@
 from typing import Any, Dict
 
 # 本地模块
-from app.main_graph.state import MainGraphState
-from app.memory.mem0_client import Mem0Client
-from app.utils.logging import log_state_change
-from app.logger import debug
+from ...main_graph.state import MainGraphState
+from ...memory.mem0_client import Mem0Client
+from ...utils.logging import log_state_change
+from ...logger import debug
 
 
 def create_retrieve_memory_node(mem0_client: Mem0Client):
@@ -67,10 +67,10 @@ def create_retrieve_memory_node(mem0_client: Mem0Client):
                 else:
                     debug("🔍 [记忆检索] 未找到相关记忆")
             except Exception as e:
-                from app.logger import warning
+                from backend.app.logger import warning
                 warning(f"⚠️ Mem0 检索失败: {e}")
         else:
-            from app.logger import warning
+            from backend.app.logger import warning
             warning("⚠️ Mem0 未初始化，跳过记忆检索")
 
         memory_context = "\n\n".join(memory_text_parts) if memory_text_parts else "暂无用户信息"

backend/app/main_graph/nodes/routing.py

@@ -10,9 +10,9 @@
 
 from datetime import datetime
 
-from app.core.intent import get_route_by_reasoning, ReasoningAction
-from app.main_graph.state import MainGraphState
-from app.logger import info
+from ...core.intent import get_route_by_reasoning, ReasoningAction
+from ...main_graph.state import MainGraphState
+from ...logger import info
 
 
 # ========== 初始化状态节点 ==========

backend/app/main_graph/nodes/summarize.py

@@ -6,10 +6,10 @@
 from typing import Any, Dict
 
 # 本地模块
-from app.main_graph.state import MainGraphState
-from app.memory.mem0_client import Mem0Client
-from app.utils.logging import log_state_change
-from app.logger import debug, info, error, warning
+from ...main_graph.state import MainGraphState
+from ...memory.mem0_client import Mem0Client
+from ...utils.logging import log_state_change
+from ...logger import debug, info, error, warning
 
 
 def create_summarize_node(mem0_client: Mem0Client):

backend/app/main_graph/nodes/tool_call.py

@@ -6,12 +6,12 @@
 import asyncio
 from typing import Any, Dict
 from langchain_core.messages import AIMessage, ToolMessage
-from app.main_graph.config import get_stream_writer
+from ...main_graph.config import get_stream_writer
 
 # 本地模块
-from app.main_graph.state import MainGraphState
-from app.utils.logging import log_state_change
-from app.logger import debug, info
+from ...main_graph.state import MainGraphState
+from ...utils.logging import log_state_change
+from ...logger import debug, info
 
 def create_tool_call_node(tools_by_name: Dict[str, Any]):
     """

backend/app/main_graph/nodes/web_search.py

@@ -2,14 +2,15 @@
 联网搜索节点 - 执行搜索并将结果保存到状态
 """
 
-from typing import Dict, Any, Optional
+from typing import Optional
 from datetime import datetime
+from langchain_core.runnables.config import RunnableConfig
 
-from app.main_graph.state import MainGraphState, ErrorRecord, ErrorSeverity
-from app.logger import info
+from ...main_graph.state import MainGraphState, ErrorRecord, ErrorSeverity
+from ...logger import info
 
 
-async def web_search_node(state: MainGraphState, config: Optional[Dict[str, Any]] = None) -> MainGraphState:
+async def web_search_node(state: MainGraphState, config: Optional[RunnableConfig] = None) -> MainGraphState:
     """
     联网搜索节点：执行搜索并将结果保存到状态
     """
@@ -39,7 +40,7 @@ async def web_search_node(state: MainGraphState, config: Optional[Dict[str, Any]
     search_query = reasoning_result.metadata.get("search_query", state.user_query) if reasoning_result else state.user_query
 
     try:
-        from app.core import web_search
+        from backend.app.core import web_search
 
         print(f"[WebSearch] 搜索: {search_query}")
         search_result = web_search(search_query, max_results=5)